In order to reconstruct a color image it is usually necessary to carry out an operation known as color interpolation (or demosaicing) to generate triplets of base color values (RGB) or more values, one for each base hue, through appropriate interpolation algorithms for generating values of missing colors for each image pixel. Numerous techniques for processing data provided by a digital color sensor have been proposed. It is worth mentioning the following documents: M. R. Gupta, T. Chen, “Vector Color Filter Array Demosaicing” SPIE Electronic Imaging 2001; R. Ramanath, W. E. Snyder, G. L. Bilbro, W. A. Sander, “Demosaicing Methods for Bayer Color Arrays”, Journal of Electronic Imaging, vol. 11, n. 3, pages 306-315, July 2002; R. Kimmel, “Demosaicing: Image Reconstruction from Color CCD Samples”; R. Kakarala, Z. Baharav, “Adaptive Demosaicing with The Principal Vector Method”, IEEE Transactions on Consumer Electronics, vol. 48, n. 4, pages 932-937, November 2002; B. E. Bayer, “Color Imaging Array”, U.S. Pat. No. 3,971,065, July 1976; B. K. Gunturk, Y. Altunbasak, R, Mersereau, “Color Plane Interpolation Using Alternating Projections”, IEEE Transactions on Image Processing, vol. 11, no. 9, pages 997-1013, September 2002; S. Smith, “Colour Image Restoration with Anti-Alias”, EP 1,098,535, May 2001. Many known techniques preliminarily subdivide the image data stream generated by the digital color sensor into two or more channels, such as three channels for the case of a filtering based upon the RGB triplet of primary colors (red, green, blue). When the red component of a pixel is to be estimated, but only its green level has been acquired, it is necessary to estimate the red pixels adjacent to the considered pixel, and so on, when the value of another missing color is to be estimated. Clearly, subdividing in different channels grey level data generated by the digital color sensor and the successive merging operation of the values calculated for primary colors or base hues with the known value of the primary color of base hue for the considered pixel implies an evident computational burden or, in case of hardware implementation, an increased circuit complexity.
The development of new consumer applications of digital photo-cameras and similar devices, for instance in cellular phones, in laptop (notebook) or hand-held computers, and other devices for mobile communications, encourages the need to devise more effective and at the same time low cost techniques for processing images acquired by a digital color sensor. A particular important factor is the low cost, because these techniques may desirably be used in devices economically accessible to individual consumers, and there is considerable competition in this field among manufacturers of these devices and their components.